3 citations · 3 across the 3 of their papers we have counts for
4 papers
Imagining Goals with Geometric Horizon Models for Policy Generalization
Daniel Lawson, Dhruv Sreenivas, Adriana Hugessen +2
Training from offline data has allowed for substantial progress in domains such as robotics, leading to general-purpose policies that can be easily applied zero-shot or efficiently…
Self-Predictive Representations for Combinatorial Generalization in Behavioral Cloning
Daniel Lawson, Adriana Hugessen, Charlotte Cloutier +2
While goal-conditioned behavior cloning (GCBC) methods can perform well on in-distribution training tasks, they do not necessarily generalize zero-shot to tasks that require condit…
Surprise-Adaptive Intrinsic Motivation for Unsupervised Reinforcement Learning
Adriana Hugessen, Roger Creus Castanyer, Faisal Mohamed +1
Both entropy-minimizing and entropy-maximizing (curiosity) objectives for unsupervised reinforcement learning (RL) have been shown to be effective in different environments, depend…
Searching for High-Value Molecules Using Reinforcement Learning and Transformers
Raj Ghugare, Santiago Miret, Adriana Hugessen +2
Reinforcement learning (RL) over text representations can be effective for finding high-value policies that can search over graphs. However, RL requires careful structuring of the…